Workload Characterization and Traffic Analysis for Reconfigurable Intelligent Surfaces within 6G Wireless Systems
(2023) In IEEE Transactions on Mobile Computing 22(5). p.3079-3094- Abstract
- Programmable metasurfaces constitute an emerging paradigm, envisaged to become a key enabling technology for Reconfigurable Intelligent Surfaces (RIS) due to their powerful control over electromagnetic waves. The HyperSurface (HSF) paradigm takes one step further by embedding a network of customized integrated circuit (IC) controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that the network needs to support as the target electromagnetic function or boundary conditions change. In this paper, the framework of a methodology is introduced to characterize the workload of programmable metasurfaces which is then used to analyze the beam steering HSFs. The... (More)
- Programmable metasurfaces constitute an emerging paradigm, envisaged to become a key enabling technology for Reconfigurable Intelligent Surfaces (RIS) due to their powerful control over electromagnetic waves. The HyperSurface (HSF) paradigm takes one step further by embedding a network of customized integrated circuit (IC) controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that the network needs to support as the target electromagnetic function or boundary conditions change. In this paper, the framework of a methodology is introduced to characterize the workload of programmable metasurfaces which is then used to analyze the beam steering HSFs. The workload characterization leads to many useful insights into traffic behavior, including the spatio-temporal load incurred and the HSF limitations in terms of fine-grained tracking of moving targets. It is observed that the traffic is inherently bursty with an uneven spatial distribution of load and that finer resolution comes at the cost of an increased but less bursty load. An indoor mobility model indicates reasonable signaling load on the deployed surfaces. Finally, a statistical analysis on the traffic patterns is performed, showing that the incoming traffic can be well represented by an ON-OFF model. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1fbfc7df-cb85-4b2e-bd0e-99fcedf23881
- author
- Saeed, Taqwa LU ; Abadal, Sergi ; Liaskos, Christos ; Pitsillides, Andreas ; Taghvaee, Hamidrez ; Cabellos-Aparicio, Albert ; Soteriou, Vassos ; Alarcon, Eduard ; Akylidiz, Ian and Lestas, Marios
- publishing date
- 2023
- type
- Contribution to journal
- publication status
- published
- subject
- in
- IEEE Transactions on Mobile Computing
- volume
- 22
- issue
- 5
- pages
- 17 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:85118608807
- ISSN
- 1536-1233
- DOI
- 10.1109/TMC.2021.3124638
- language
- English
- LU publication?
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- id
- 1fbfc7df-cb85-4b2e-bd0e-99fcedf23881
- date added to LUP
- 2023-03-17 11:53:14
- date last changed
- 2023-10-26 15:00:28
@article{1fbfc7df-cb85-4b2e-bd0e-99fcedf23881,
abstract = {{Programmable metasurfaces constitute an emerging paradigm, envisaged to become a key enabling technology for Reconfigurable Intelligent Surfaces (RIS) due to their powerful control over electromagnetic waves. The HyperSurface (HSF) paradigm takes one step further by embedding a network of customized integrated circuit (IC) controllers within the device with the aim of adding intelligence, connectivity, and autonomy. However, little is known about the traffic that the network needs to support as the target electromagnetic function or boundary conditions change. In this paper, the framework of a methodology is introduced to characterize the workload of programmable metasurfaces which is then used to analyze the beam steering HSFs. The workload characterization leads to many useful insights into traffic behavior, including the spatio-temporal load incurred and the HSF limitations in terms of fine-grained tracking of moving targets. It is observed that the traffic is inherently bursty with an uneven spatial distribution of load and that finer resolution comes at the cost of an increased but less bursty load. An indoor mobility model indicates reasonable signaling load on the deployed surfaces. Finally, a statistical analysis on the traffic patterns is performed, showing that the incoming traffic can be well represented by an ON-OFF model.}},
author = {{Saeed, Taqwa and Abadal, Sergi and Liaskos, Christos and Pitsillides, Andreas and Taghvaee, Hamidrez and Cabellos-Aparicio, Albert and Soteriou, Vassos and Alarcon, Eduard and Akylidiz, Ian and Lestas, Marios}},
issn = {{1536-1233}},
language = {{eng}},
number = {{5}},
pages = {{3079--3094}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Mobile Computing}},
title = {{Workload Characterization and Traffic Analysis for Reconfigurable Intelligent Surfaces within 6G Wireless Systems}},
url = {{http://dx.doi.org/10.1109/TMC.2021.3124638}},
doi = {{10.1109/TMC.2021.3124638}},
volume = {{22}},
year = {{2023}},
}